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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="preprocessor">#ifndef CAFFE_SIGMOID_CROSS_ENTROPY_LOSS_LAYER_HPP_</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="preprocessor">#define CAFFE_SIGMOID_CROSS_ENTROPY_LOSS_LAYER_HPP_</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;</div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="preprocessor">#include &lt;vector&gt;</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;caffe/blob.hpp&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;caffe/layer.hpp&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;caffe/proto/caffe.pb.h&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &quot;caffe/layers/loss_layer.hpp&quot;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &quot;caffe/layers/sigmoid_layer.hpp&quot;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacecaffe.html">caffe</a> {</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Dtype&gt;</div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html">   45</a></span>&#160;<span class="keyword">class </span><a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html">SigmoidCrossEntropyLossLayer</a> : <span class="keyword">public</span> <a class="code" href="classcaffe_1_1LossLayer.html">LossLayer</a>&lt;Dtype&gt; {</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160; <span class="keyword">public</span>:</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;  <span class="keyword">explicit</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html">SigmoidCrossEntropyLossLayer</a>(<span class="keyword">const</span> LayerParameter&amp; param)</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;      : <a class="code" href="classcaffe_1_1LossLayer.html">LossLayer&lt;Dtype&gt;</a>(param),</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;          <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a69e0c8d2106b4b06c7c896e3069f531c">sigmoid_layer_</a>(<span class="keyword">new</span> <a class="code" href="classcaffe_1_1SigmoidLayer.html">SigmoidLayer&lt;Dtype&gt;</a>(param)),</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;          <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a1eb4c2e90dd4807dbfb0806a411a7bea">sigmoid_output_</a>(<span class="keyword">new</span> <a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>()) {}</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#aa1535140dd4eb94557c3afc89076d56d">LayerSetUp</a>(<span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; bottom,</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;      <span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; top);</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a305423abeea4bd1652ff7e696aaba808">Reshape</a>(<span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; bottom,</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;      <span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; top);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a38dd36e04f37f4692446b057a48e96e1">   56</a></span>&#160;  <span class="keyword">virtual</span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a38dd36e04f37f4692446b057a48e96e1">type</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <span class="stringliteral">&quot;SigmoidCrossEntropyLoss&quot;</span>; }</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160; <span class="keyword">protected</span>:</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#aa3e7f285742d862435d5e49d13e05064">Forward_cpu</a>(<span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; bottom,</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;      <span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; top);</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a3a973821a2a73fd8bf4c2e474b2ad5d8">Forward_gpu</a>(<span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; bottom,</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;      <span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; top);</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a025360b1de1fefbc4684e43603394a22">Backward_cpu</a>(<span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; top,</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;      <span class="keyword">const</span> vector&lt;bool&gt;&amp; propagate_down, <span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; bottom);</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a3e1aa9138092aad788dc72fef27041f2">Backward_gpu</a>(<span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; top,</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;      <span class="keyword">const</span> vector&lt;bool&gt;&amp; propagate_down, <span class="keyword">const</span> vector&lt;<a class="code" href="classcaffe_1_1Blob.html">Blob&lt;Dtype&gt;</a>*&gt;&amp; bottom);</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  <span class="keyword">virtual</span> Dtype <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#af8ce9b84227c0be01d4a1cc248a7aa52">get_normalizer</a>(</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;      LossParameter_NormalizationMode normalization_mode, <span class="keywordtype">int</span> valid_count);</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a69e0c8d2106b4b06c7c896e3069f531c">  108</a></span>&#160;  shared_ptr&lt;SigmoidLayer&lt;Dtype&gt; &gt; <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a69e0c8d2106b4b06c7c896e3069f531c">sigmoid_layer_</a>;</div><div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a1eb4c2e90dd4807dbfb0806a411a7bea">  110</a></span>&#160;  shared_ptr&lt;Blob&lt;Dtype&gt; &gt; <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a1eb4c2e90dd4807dbfb0806a411a7bea">sigmoid_output_</a>;</div><div class="line"><a name="l00112"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a52c3183799d44aa9e581992aee502409">  112</a></span>&#160;  vector&lt;Blob&lt;Dtype&gt;*&gt; <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a52c3183799d44aa9e581992aee502409">sigmoid_bottom_vec_</a>;</div><div class="line"><a name="l00114"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#af6719c9685fcf910129db20cceb47be5">  114</a></span>&#160;  vector&lt;Blob&lt;Dtype&gt;*&gt; <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#af6719c9685fcf910129db20cceb47be5">sigmoid_top_vec_</a>;</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a7e2ebf45542532439096caaec42a2a85">  117</a></span>&#160;  <span class="keywordtype">bool</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a7e2ebf45542532439096caaec42a2a85">has_ignore_label_</a>;</div><div class="line"><a name="l00119"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#ab99d98ce823df6c90cd4c3cf8b0a793f">  119</a></span>&#160;  <span class="keywordtype">int</span> <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#ab99d98ce823df6c90cd4c3cf8b0a793f">ignore_label_</a>;</div><div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#ad4e3c7105f896bd7792e53ef3a0a2dd8">  121</a></span>&#160;  LossParameter_NormalizationMode <a class="code" href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#ad4e3c7105f896bd7792e53ef3a0a2dd8">normalization_</a>;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;  Dtype normalizer_;</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;  <span class="keywordtype">int</span> outer_num_, inner_num_;</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;};</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;}  <span class="comment">// namespace caffe</span></div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;<span class="preprocessor">#endif  // CAFFE_SIGMOID_CROSS_ENTROPY_LOSS_LAYER_HPP_</span></div><div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a52c3183799d44aa9e581992aee502409"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a52c3183799d44aa9e581992aee502409">caffe::SigmoidCrossEntropyLossLayer::sigmoid_bottom_vec_</a></div><div class="ttdeci">vector&lt; Blob&lt; Dtype &gt; * &gt; sigmoid_bottom_vec_</div><div class="ttdoc">bottom vector holder to call the underlying SigmoidLayer::Forward </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:112</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_aa3e7f285742d862435d5e49d13e05064"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#aa3e7f285742d862435d5e49d13e05064">caffe::SigmoidCrossEntropyLossLayer::Forward_cpu</a></div><div class="ttdeci">virtual void Forward_cpu(const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;bottom, const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;top)</div><div class="ttdoc">Computes the cross-entropy (logistic) loss , often used for predicting targets interpreted as probabi...</div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.cpp:79</div></div>
<div class="ttc" id="namespacecaffe_html"><div class="ttname"><a href="namespacecaffe.html">caffe</a></div><div class="ttdoc">A layer factory that allows one to register layers. During runtime, registered layers can be called b...</div><div class="ttdef"><b>Definition:</b> blob.hpp:14</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidLayer_html"><div class="ttname"><a href="classcaffe_1_1SigmoidLayer.html">caffe::SigmoidLayer</a></div><div class="ttdoc">Sigmoid function non-linearity , a classic choice in neural networks. </div><div class="ttdef"><b>Definition:</b> sigmoid_layer.hpp:23</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a1eb4c2e90dd4807dbfb0806a411a7bea"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a1eb4c2e90dd4807dbfb0806a411a7bea">caffe::SigmoidCrossEntropyLossLayer::sigmoid_output_</a></div><div class="ttdeci">shared_ptr&lt; Blob&lt; Dtype &gt; &gt; sigmoid_output_</div><div class="ttdoc">sigmoid_output stores the output of the SigmoidLayer. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:110</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_af6719c9685fcf910129db20cceb47be5"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#af6719c9685fcf910129db20cceb47be5">caffe::SigmoidCrossEntropyLossLayer::sigmoid_top_vec_</a></div><div class="ttdeci">vector&lt; Blob&lt; Dtype &gt; * &gt; sigmoid_top_vec_</div><div class="ttdoc">top vector holder to call the underlying SigmoidLayer::Forward </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:114</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_ad4e3c7105f896bd7792e53ef3a0a2dd8"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#ad4e3c7105f896bd7792e53ef3a0a2dd8">caffe::SigmoidCrossEntropyLossLayer::normalization_</a></div><div class="ttdeci">LossParameter_NormalizationMode normalization_</div><div class="ttdoc">How to normalize the loss. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:121</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_af8ce9b84227c0be01d4a1cc248a7aa52"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#af8ce9b84227c0be01d4a1cc248a7aa52">caffe::SigmoidCrossEntropyLossLayer::get_normalizer</a></div><div class="ttdeci">virtual Dtype get_normalizer(LossParameter_NormalizationMode normalization_mode, int valid_count)</div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.cpp:49</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a69e0c8d2106b4b06c7c896e3069f531c"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a69e0c8d2106b4b06c7c896e3069f531c">caffe::SigmoidCrossEntropyLossLayer::sigmoid_layer_</a></div><div class="ttdeci">shared_ptr&lt; SigmoidLayer&lt; Dtype &gt; &gt; sigmoid_layer_</div><div class="ttdoc">The internal SigmoidLayer used to map predictions to probabilities. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:108</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_aa1535140dd4eb94557c3afc89076d56d"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#aa1535140dd4eb94557c3afc89076d56d">caffe::SigmoidCrossEntropyLossLayer::LayerSetUp</a></div><div class="ttdeci">virtual void LayerSetUp(const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;bottom, const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;top)</div><div class="ttdoc">Does layer-specific setup: your layer should implement this function as well as Reshape. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.cpp:10</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a7e2ebf45542532439096caaec42a2a85"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a7e2ebf45542532439096caaec42a2a85">caffe::SigmoidCrossEntropyLossLayer::has_ignore_label_</a></div><div class="ttdeci">bool has_ignore_label_</div><div class="ttdoc">Whether to ignore instances with a certain label. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:117</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a38dd36e04f37f4692446b057a48e96e1"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a38dd36e04f37f4692446b057a48e96e1">caffe::SigmoidCrossEntropyLossLayer::type</a></div><div class="ttdeci">virtual const char * type() const</div><div class="ttdoc">Returns the layer type. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:56</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a3e1aa9138092aad788dc72fef27041f2"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a3e1aa9138092aad788dc72fef27041f2">caffe::SigmoidCrossEntropyLossLayer::Backward_gpu</a></div><div class="ttdeci">virtual void Backward_gpu(const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;top, const vector&lt; bool &gt; &amp;propagate_down, const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;bottom)</div><div class="ttdoc">Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_...</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a305423abeea4bd1652ff7e696aaba808"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a305423abeea4bd1652ff7e696aaba808">caffe::SigmoidCrossEntropyLossLayer::Reshape</a></div><div class="ttdeci">virtual void Reshape(const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;bottom, const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;top)</div><div class="ttdoc">Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs...</div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.cpp:36</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html">caffe::SigmoidCrossEntropyLossLayer</a></div><div class="ttdoc">Computes the cross-entropy (logistic) loss , often used for predicting targets interpreted as probabi...</div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:45</div></div>
<div class="ttc" id="classcaffe_1_1LossLayer_html"><div class="ttname"><a href="classcaffe_1_1LossLayer.html">caffe::LossLayer</a></div><div class="ttdoc">An interface for Layers that take two Blobs as input – usually (1) predictions and (2) ground-truth ...</div><div class="ttdef"><b>Definition:</b> loss_layer.hpp:23</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a3a973821a2a73fd8bf4c2e474b2ad5d8"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a3a973821a2a73fd8bf4c2e474b2ad5d8">caffe::SigmoidCrossEntropyLossLayer::Forward_gpu</a></div><div class="ttdeci">virtual void Forward_gpu(const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;bottom, const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;top)</div><div class="ttdoc">Using the GPU device, compute the layer output. Fall back to Forward_cpu() if unavailable. </div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_a025360b1de1fefbc4684e43603394a22"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#a025360b1de1fefbc4684e43603394a22">caffe::SigmoidCrossEntropyLossLayer::Backward_cpu</a></div><div class="ttdeci">virtual void Backward_cpu(const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;top, const vector&lt; bool &gt; &amp;propagate_down, const vector&lt; Blob&lt; Dtype &gt; *&gt; &amp;bottom)</div><div class="ttdoc">Computes the sigmoid cross-entropy loss error gradient w.r.t. the predictions. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.cpp:104</div></div>
<div class="ttc" id="classcaffe_1_1Blob_html"><div class="ttname"><a href="classcaffe_1_1Blob.html">caffe::Blob</a></div><div class="ttdoc">A wrapper around SyncedMemory holders serving as the basic computational unit through which Layers...</div><div class="ttdef"><b>Definition:</b> blob.hpp:24</div></div>
<div class="ttc" id="classcaffe_1_1SigmoidCrossEntropyLossLayer_html_ab99d98ce823df6c90cd4c3cf8b0a793f"><div class="ttname"><a href="classcaffe_1_1SigmoidCrossEntropyLossLayer.html#ab99d98ce823df6c90cd4c3cf8b0a793f">caffe::SigmoidCrossEntropyLossLayer::ignore_label_</a></div><div class="ttdeci">int ignore_label_</div><div class="ttdoc">The label indicating that an instance should be ignored. </div><div class="ttdef"><b>Definition:</b> sigmoid_cross_entropy_loss_layer.hpp:119</div></div>
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